A Smart Electromechanical Actuator Monitor for New Model-Based Prognostic Algorithms

Prognostic algorithms able to identify precursors of incipient failures of primary flight command electromechanical actuators (EMAs) are beneficial for the anticipation of the incoming fault: an early and correct interpretation of the degradation pattern, in fact, can trig an early alert of the maintenance crew, who can properly schedule the servomechanism replacement. Given that very often these algorithms exploit a model-based approach (e.g. directly comparing the monitor with the real system or using it to identify the fault parameters by means of optimization processes), the design and development of appropriate monitoring models, able to combine simplicity, reduced computational effort and a satisfactory level of sensitivity and accuracy, becomes a fundamental and unavoidable step of the prognostic process. To this purpose, the authors propose a new simplified EMA Monitor Model able to accurately reproduce the dynamic response of the Reference Model in terms of position, speed and equivalent current, even with the presence of various incipient faults; its ability in reproducing the effects of several EMA faults is a good starting point for the implementation of a robust and accurate GA-based optimization, leading to a reliable and early fault isolation.